Several aspects deserve attention in the perspective of building
the ML potential. First of all, the choice of the exchange and
correlation (XC) functional for the electronic structure calculations
is crucial. As the ML potential may reach an accuracy
similar to the DFT calculations, it will mirror the ability of the
XC functional used in predicting the properties, at least in the
thermodynamic domain inside which it was trained. This has guided
our choice of the Local Density Approximation (LDA) functional given
the fact that the Generalized-Gradient-Approximation (GGA) overestimate
the atomic volume [1]}. Moreover, it was shown in our
previous contributions that the LDA gives a good description of the
liquid structure [2]}. More importantly, atomic transport
properties such as the selfdiffusion coefficient, which are very
sensitive to the details of the potentials, are well reproduced
within the LDA compared to state-of-the-art experimental data
[3]}, [4]}. Such a good agreement with experiments
was very recently confirmed on the dynamic structure factors as
well as the structural relaxation times extracted from the
self-intermediate scattering function [5]}. For high
pressures, it was shown [6]} that the difference
between LDA and GGA [7]} is negligible in describing
the pressure-density phase diagram of aluminium up to pressures as
high as 10 TPa.
